High expression of GPR176 predicts poor prognosis of gastric cancer patients and promotes the proliferation, migration, and invasion of gastric cancer cells

G-protein-coupled receptors (GPCRs) are the most prominent family of cell surface receptors, which can regulate various biological functions and play an essential role in many diseases. GPR176 is a member of the GPCRs family and has been rarely studied in cancer. We aim to investigate the diagnostic and prognostic value of GPR176 in gastric cancer (GC) and explore its potential mechanism. Through the TCGA database and real-time quantitative PCR, we found that the expression level of GPR176 was significantly increased in GC and had good value in the diagnosis and prognosis of GC. Vitro experiments revealed that GPR176 could promote the proliferation, migration, and invasion of GC cells and may be involved in regulating multiple tumors and immune-related signaling pathways. In addition, we found that GPR176 is associated with GC immune infiltration and may affect the immune efficacy of GC patients. In summary, the high GPR176 expression level was associated with poor prognosis, more robust immune infiltration, and worse immunotherapy efficacy in GC patients, suggesting that GPR176 may be an immune-related biomarker for GC that can promote the proliferation, migration, and invasion of GC cells.

Transwell assay for cell migration and invasion. 5 × 10 4 cells were inoculated in the upper chamber and a complete medium containing 20% fetal bovine serum was added to the lower chamber 17 . The number of cells entering the lower chamber was counted to reflect the migration ability of the tumor cells. Before the invasion assay, a layer of stromal gel was placed in the upper chamber and 8 × 10 4 cells were inoculated into the lower chamber after the stromal gel had solidified 18 , the number of cells entering the lower chamber could reflect the invasion ability of the cells.
Total RNA extraction, reverse transcription, and Real-time quantitative PCR (RT-qPCR). TRIzol Reagent (Invitrogen, Germany) was used to extract the total RNA of tissue specimens, and Revert Aid RT Reverse Transcription Kit (ThermoFisher Scientific, USA) was used to produce cDNA. RT-qPCR was performed on ABI QuantStudio5 with 10 μL ChamQ Universal SYBR qPCR Master Mix (Vazyme Biotech Co., Ltd, China), 0.5 μL primers (10 μM), 4 μL enzyme-free Water and 5 μL cDNA. GAPDH was used as an internal reference, and the expression of GPR176 was calculated by the 2 −∆∆CT method. The sequences of primer used in this study were GPR176-F: GAT GGT CTT CAT CTT GTG TAGC, GPR176-R: CTC CCT GTA CTG ACC ACA TTAC; GAPDH-F: AGA AGG CTG GGG CTC ATT TG, GAPDH-R: GCA GGA GGC ATT GCT GAT GAT.
The Human Protein Atlas. Comparison of GPR176 protein expression between Stomach adenocarcinoma (STAD) and normal gastric tissues was performed using the immunohistochemistry images on The Human Protein Atlas (https:// www. prote inatl as. org) 19 .

Construction of the protein-protein interaction (PPI) network. The protein-protein interaction
(PPI) network of GPR176 was constructed using GeneMANIA (http:// genem ania. org/), which can use a very large set of functional association data to find other genes associated with the target gene 20 .

Functional enrichment analysis. Gene Set Enrichment Analysis (GSEA).
We divided GC patients into high and low expression groups based on the expression level of GPR176 and identified the pathways enriched to GPR176 in GC by GSEA v4.2.3 downloaded from GSEA (https:// www. gsea-msigdb. org/ gsea/ index. jsp). The gene sets 'c2.cp.kegg.v7.5.1.symbols.gmt' from the Molecular Signature Database (MSigDB) was used as the reference for GSEA, and the P-value < 0.05 and q-value < 0.25 were considered with significant differences.
Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. The R package "tidyverse", "clusterProfiler", and "org.Hs.eg.db" were used to perform GO and KEGG analyses on GPR176, and the P-value < 0.05 and q-value < 0.05 were considered with significant differences.
Tumor immune infiltration analysis. Tumor immune estimation resource (TIMER) is a comprehensive resource for systematical analysis of immune infiltrates across diverse cancer types and TIMER2.0 (http:// timer. cistr ome. org/) is an updated version of TIMER 21 . We analyzed the correlation between GPR176 and six different immune cells using TIMER2.0.
The CIBERSORT method was used to estimate the abundance of tumor-infiltrating immune cells from the gene expression profiles in all STAD samples 22 .
The single-sample gene set enrichment analysis (ssGSEA) method from the R package "GSVA" was used to calculate the degree of infiltration of 28 immune cell types between two groups based on the published expression levels of 28 immune cell genomes 23,24 .
ESTIMATE is a method that uses gene expression to infer the ratio of stromal to immune cells in tumor specimens 25 . We used this method to assess the immune score, stromal score, ESTIMATE score, and tumor purity of each STAD sample.
We downloaded the normalized pan-cancer dataset from the UCSC database and extracted GPR176, 150 genes from the five classes of immune pathways (chemokine, receptor, MHC, Immunoinhibitor, Immunostimulator), and 60 genes from the two classes of immune checkpoint pathways (Inhibitory, Stimulatory) 26 expression data for marker genes in individual samples. Then, we performed the correlation analysis by Spearman's analysis.
Prediction of immunotherapy efficacy. Tumor Immune Dysfunction and Exclusion (TIDE, http:// tide. dfci. harva rd. edu/) allows for the calculation of a TIDE score that negatively correlates with the efficacy of immunotherapy by modeling the mechanism of tumor immune escape through the expression profile of genes in the tumor. We calculated the TIDE score for STAD patients using TIDE and compared it to the expression level of GPR176.
The Cancer Immunome Database (TCIA, https:// tcia. at/ home) provides results of comprehensive immunogenomic analyses for 20 solid cancers from TCGA and other data sources 27 . We predicted the immunogenicity of patients with different expression levels of GPR176 to immunotherapy using TCIA. Data analysis. All data in the study were first checked for normality, and were expressed as the mean ± standard deviation. A t-test or Mann-Whitney U test was used to analyze the expression level of GPR176 in two dependent groups. Paired t-tests or Wilcoxon test was used for paired samples and the expression level of GPR176 in GC cells were compared using one-way analysis of variance (ANOVA). The R package "survival" was used to perform survival analysis in two groups, and the log-rank test was used to assess the significance of prognostic differences between different groups. Univariate and multivariate Cox regression analyses were performed to assess the relationship of GPR176 and other clinicopathological parameters with the prognosis of GC patients. The R package "regression modeling strategies (rms)" was used to plot nomograms. All analyses of correlation were performed using Spearman's analysis. The P-value < 0.05 and r > 0.3 was considered significant and positively correlated.

Results
The expression level of GPR176 in GC and its diagnostic and prognostic value. As shown in For follow-up research, we focused on GC and found high GPR176 expression in various GC cell lines (Fig. 1b). To further explore the diagnostic value of GPR176 in GC, we analyzed the expression levels of GPR176 in the TCGA STAD database and found that it was significantly higher in GC tissues (n = 373) than in adjacent normal tissues of cancer (n = 32; P < 0.001; Fig. 1c, d). Receiver operating characteristic curve (ROC) analysis showed that the area under the curve (AUC) of GPR176 was 0.840, demonstrating its good diagnostic efficacy in GC (Fig. 1e). Then, we collected 50 pairs of GC tissues and their adjacent non-tumor tissues. The RT-qPCR results showed that the expression level of GPR176 was significantly increased in GC tissues (P < 0.001; Fig. 1f, g) and the AUC was 0.714 ( Fig. 1h), which was consistent with the results of the TCGA STAD database. Kaplan-Meier survival analysis showed that the overall survival (OS) was lower in the high GPR176 group compared to the low GPR176 group (Fig. 1i, j). In addition, immunohistochemistry showed deeper staining levels of GPR176 in GC tissues than in normal gastric tissues, indicating higher protein levels of GPR176 in GC tissues (Fig. 1k). Taken together, the increased expression of GPR176 in GC correlated with poor prognosis, suggesting that it may be a critical gene that could be used to differentiate GC patients clinically.
Correlation of GPR176 with clinicopathological parameters and is an independent prognostic factor for GC. By analyzing the correlation between GPR176 and clinicopathological parameters in GC, we found that GPR176 was significantly associated with the depth of infiltration and survival status. At the same time, there was no significant relationship with other pathological parameters (see Supplementary  Table S1 Table 1). Multivariate analysis showed that GPR176 (HR = 1.80, P = 0.003), residual tumor (HR = 2.81, P < 0.001), and age (HR = 1.55, P = 0.027) were independent prognostic factors for GC (see Supplementary Fig. S1b online, Table 1).

Establishing nomogram for predicting prognosis of OS for GC patients.
To predict the prognostic OS of GC patients, we constructed a Nomogram prognostic model with clinicopathological parameters and GPR176. In this model, a score is defined for each risk factor, and we can predict the OS of the patient based on the total score (the sum of the scores of all risk factors) for each patient: the higher the total score, the lower the OS (Fig. 2a). In addition, the AUC of the 1-year, 3-year, and 5-year ROC curves of the line graph prognostic model were 0.736, 0.734, and 0.733, respectively ( Fig. 2b-d), and the calibration curves showed a high degree of fit between the actual and predicted OS without deviation from the reference line ( Fig. 3e-g). The above results indicate that the Nomogram prognostic model we constructed has good accuracy and confidence in predicting the OS of GC patients.

Functional and pathway prediction of GPR176 in GC.
To investigate the potential mechanisms by which GPR176 affects GC, we performed KEGG biological pathway enrichment analysis and GO gene function enrichment analysis on the differentially expressed genes according to GPR176 expression levels. KEGG analysis showed that the genes were significantly enriched in the pathways of Protein digestion and absorption, Neuroactive ligand-receptor Interaction, and Extracellular matrix-receptor interaction (Fig. 3a). The results of GO analysis showed that Biological Process (BP) was enriched considerably in internal encapsulating structure organization, extracellular matrix organization, and extracellular structure organization. In Cellular Component (CC), collagen-containing extracellular matrix, collagen trimer, and contractile fiber were significantly enriched, while in Molecular Function (MF), extracellular matrix structural constituent, collagen binding, and glycosaminogly-    www.nature.com/scientificreports/ can binding were significantly enriched (Fig. 3b). GSEA showed that compared to the GPR176 low expression group, the GPR176 high expression group was enriched considerably in two cancer-related signaling pathways: TGF_BETA_SIGNALING_PATHWAY, MAPK_SIGNALING_PATHWAY, and four immune-related signaling pathways: COMPLEMENT_AND_COAGULATION_CASCADES, CHEMOKINE_SIGNALING_PATHWAY, CYTOKINE_CYTOKINE_RECEPTOR_INTERACTION, and JAK_STAT_SIGNALING_PATHWAY (Fig. 3c, see Supplementary Table S2 online). It suggested that GPR176 plays a role in GC progression and tumor immunity.

GPR176 promotes GC cell proliferation, migration, and invasion abilities. To investigate whether
GPR176 is involved in regulating GC progression, we verified its impact on GC cell proliferation, migration, and invasion abilities in vitro. We first detected the expression level of GPR176 in GC cells, and the results showed that it was significantly increased in HGC-27 and MKN-1 (Fig. 4a). CCK8 and clone formation assays showed that the knockdown of GPR176 significantly decreased the proliferation ability of GC cells (Fig. 4b-e). When GPR176 was knocked down, GC cells showed a considerable reduction in migration and invasion abilities (Fig. 4f, g). The above results suggest that GPR176 can promote the proliferation, migration, and invasion of GC cells.

Correlation of GPR176 with TMB and MSI and construction of PPI networks.
To explore the intrinsic mechanisms of GPR176 involvement in the regulation of GC, we constructed a PPI network of GPR176 using the GeneMANIA database (see Supplementary Fig. S2a online). It has been reported that TMB and MSI are closely related to tumor progression and have the potential to be tumor biomarkers 28,29 . We found a significant negative correlation between GPR176 and TMB and MSI in GC, suggesting that GPR176 may influence GC progression by regulating TMB and MSI (see Supplementary Fig. S2b online, c).

Correlation of GPR176 with the MMR genes and DNA methylation.
To further understand the role and mechanism of GPR176, we assessed the relationship between the expression levels of GPR176 and five MMR genes through the TCGA database. The results showed that GPR176 was significantly associated with MLH1, MSH6, and PMS2 in GC (see Supplementary Fig. S3a online). In tumor cells, aberrant DNA methylation is closely associated with tumor progression 30 . The expression levels of GPR176 in GC were positively correlated with two methyltransferases (see Supplementary Fig. S3b online), suggesting that GPR176 might influence GC progression by regulating DNA methylation and MMR.

Correlation of GPR176 with immune microenvironment and immune infiltration in GC.
To investigate the correlation between the expression level of GPR176 and the immune microenvironment, we analyzed the proportion of tumor immune cell subpopulations using the CIBERSORT algorithm and constructed a profile of 22 immune cell types in GC samples (Fig. 5a). CIBERSORT analysis showed a higher proportion of Monocytes in the high GPR176 expression group (Fig. 5b). In contrast, ssGSEA analysis showed that Activated B cells, Activated dendritic cells, Central memory CD4 T cells, Central memory, CD8 T cell, Effector memeory CD4 T cell, Effector memeory CD8 T cell, Eosinophil, Gamma delta T cell, Immature B cell, Immature dendritic cell Macrophage, Mast cell, MDSC, Monocyte, Natural killer cell, Natural killer T cell, Plasmacytoid dendritic cell, Regulatory T cell, T follicular helper cell, and Type 1 T helper cell were significantly higher in the high GPR176 expression group (Fig. 5c), indicating that the high GPR176 expression group has stronger immune infiltration than the low GPR176 expression group. Then, we assessed the potential relationship between the expression levels of GPR176 and GC tumor-infiltrating immune cells using the TIMER database. The results showed that the expression level of GPR176 was associated with CD8 + T cells (r = 0.447, P = 5.61e−20), Neutrophils (r = 0.439, P = 2.61e−19), Macrophages (r = 0.613, P = 1.90e−40), and dendritic cells (r = 0.417, P = 2.42e−17) were significantly positively correlated (Fig. 6a). We later analyzed the immune scores of GC samples by the ESTIMATE algorithm. We found that the high GPR176 expression group had higher stromal, immune, and ESTIMATE scores and lower tumor purity than the low GPR176 expression group (Fig. 6b-e). In addition, www.nature.com/scientificreports/ the Spearman correlation analysis showed that GPR176 expression levels were significantly positively correlated with stromal, immune, and ESTIMATE scores and negatively correlated with tumor purity (Fig. 6f-i). We further analyzed the correlation of GPR176 with common immune checkpoint genes and immune regulatory  www.nature.com/scientificreports/ genes in tumors. According to our results, GPR176 correlated significantly with immune checkpoint genes and immunomodulatory genes in GC (Fig. 6j, k), indicating that GPR176 modulates immune checkpoint genes and immunomodulatory genes to regulate immunity.
Immunotherapeutic response prediction. Next, using the TIDE database, we assessed the possible response to immunotherapy in the high and low GPR176 expression groups. The results showed that the high GPR176 expression group had a higher TIDE score, T-cell dysfunction score, T-cell exclusion score, and lower MSI score (Fig. 7a-d), suggesting that the high GPR176 expression group may have a higher rate of tumor immune escape and less effective after receiving immunotherapy. Additionally, we assessed the immunological properties of GPR176 in GC using the TCIA database. The results showed that the low GPR176 group was significantly more immunogenic to immunotherapy with CTLA4 and PD1 than the high GPR176 group (Fig. 7e, f). In conclusion, GC patients with high GPR176 expression are less effective for immunotherapy, while CTLA4 and PD1 may be potential immunotherapeutic targets for patients with low GPR176 expression.

Discussion
Recently, it has been found that the expression level of GPR176 was increased in colorectal cancer (CRC) and may promote CRC progression via inhibition of mitochondrial autophagy 31 . In addition, GPR176 was identified as a cancer-associated fibroblast marker specific to ovarian cancer and could help guide the prognostic assessment of ovarian cancer 32 . Moreover, the protein expression of GPR176 was significantly increased in breast cancer and it may serve as a potential biomarker to indicate poor prognosis of breast cancer as well as a potential target for gene therapy 33 . These findings reveal a potentially significant role for GPR176 in cancers, suggesting that it may be able to promote the malignant progression of a wide range of cancers, and perhaps has an equally indispensable role in GC. In this study, the bioinformatics analysis of GC tissues showed that GPR176 expression was significantly higher than expected. Its high expression was associated with a lower overall survival rate and had a good diagnostic and prognostic value. A previous study identified GPR176 as a potential biomarker for predicting prognosis and immune infiltration in STAD, but it was not validated using experiments 34 . Using RT-qPCR, we validated this finding and found that it was the same. Correlation analysis of clinicopathological parameters showed that high expression of GPR176 was significantly associated with the depth of infiltration and the survival status, and univariate and multifactorial analyses suggested that GPR176 might be an independent prognostic factor for GC. Additionally, we constructed a Nomogram prognostic model of GPR176 and clinicopathological parameters to predict the prognostic OS of GC patients. The above results suggest that GPR176 may be a new potential biomarker for the diagnosis and prognosis of GC. However, the specific mechanisms of GPR176 in GC have not been investigated. We found that GPR176 can promote the proliferation, migration, and invasion abilities of GC cells in vitro, indicating that high expression of GPR176 in GC may promote the malignant progression of GC. Furthermore, we predicted and constructed the PPI network of GPR176, identified many genes interacting with GPR176, and analyzed the functional pathways associated with GPR176 and the signaling pathways enriched to GPR176 by KEGG, GO, and GSEA analysis. These findings provide insight into the role of GPR176 in GC and provide ideas for future research.
Notably, the tumor microenvironment, which includes stromal cells, fibroblasts, endothelial cells, and immune cells, is complex and evolving 35 , and the ongoing interactions between the tumor microenvironment and tumor cells are closely associated with tumor progression 36,37 . Futhermore, the acquisition and maintenance of tumor proliferation, apoptosis, and invasion are closely related to Tumor microenvironment (TME) 36 . In addition, immune cells have an essential role in TME. In CRC, researchers have found that patients with stage I or stage II cancers that lack T-cell infiltration undergo recurrence within five years, while stage III patients who do have T-cell infiltration have a longer disease-free survival time 38 . Thus, finding biomarkers relating to TME and immune cells is crucial to developing new cancer therapies. Besides, we found a stronger immune infiltration  www.nature.com/scientificreports/ in the high GPR176 expression group by CIBERSORT and ssGSEA analysis and a significant positive correlation between GPR176 expression levels and CD8 + T cells, Neutrophils, Macrophages, and dendritic cells using the TIMER database, which suggests that it may influence GC progression by regulating immune cells. Immunotherapy is a massive breakthrough in cancer treatment as it aims to eliminate tumor cells by boosting their defenses 39 . However, immune checkpoints can maintain immune tolerance, and tumor cells can use immune checkpoints to escape immune surveillance to promote the malignant progression of tumors 40,41 . Tumor immunotherapy has become increasingly important with the emergence of immune checkpoint inhibitors in recent years 29 . In this study, we found that GPR176 was significantly associated with various immune checkpoint genes in GC. Furthermore, TIDE and TCIA databases were used to obtain immunological properties of GPR176 in GC. The low GPR176 expression group showed greater immunogenicity to CTLA4 and PD1 immunotherapy and possibly better efficacy.
In conclusion, although our study demonstrates the great potential of GPR176 for the diagnosis of GC, there are still some limitations to the current study. Firstly, most of our studies are based on the transcriptional level, and the detection of its protein level is also essential if it is to be better applied to the clinical diagnosis of GC. Secondly, liquid biopsy, as an emerging technique in tumor diagnosis, can greatly reduce the difficulty of diagnosis 42 . If the expression level of GPR176 mRNA in blood can be detected using RT-qPCR and its expression level is different between GC patients and healthy controls, it will certainly provide a great convenience and help in the diagnosis of GC in the future. *** ns ns ** ** ns *** *** *** *** *** *** *** ** *** *** *** ns ** *** *** ns *** *** *** *** ns ns  www.nature.com/scientificreports/ Comparison of ESTIMATE score, Immune score, Stromal score, and tumor purity between the high GPR176 group and low GPR176 group; (f-i) Correlation of the expression of GPR176 with ESTIMATE score, Immune score, Stromal score, and tumor purity; (j) Correlation analysis of GPR176 expression with the expression of immune checkpoint genes in pan-cancer; (k) Correlation analysis of GPR176 expression with the expression of immunomodulatory genes in pan-cancer (*P < 0.05, **P < 0.01, ***P < 0.001).

Conclusions
In summary, we first found that high expression of GPR176 in GC can predict poor prognosis in GC patients and is closely related to immune infiltration and efficacy. In addition, GPR176 can promote the proliferation, migration, and invasion of GC cells in vitro. Furthermore, it is significantly related to tumor-related pathways and immune-related pathways, showing its potential as a biomarker for GC and providing new possibilities for clinical screening of GC in the future.

Data availability
The data used in the current study are available from the corresponding author on reasonable request.
Received: 20 January 2023; Accepted: 6 June 2023 Figure 7. Immunotherapeutic response prediction (a-d) Comparison of TIDE score, MSI score, Dysfunction score, and Exclusion score between the high GPR176 group and low GPR176 group based on TIDE database; (e, f) Comparison of PD1 score, CTLA4 score between the high GPR176 group and low GPR176 group based on TCIA database (*P < 0.05, ***P < 0.001).